You are leading a distributed agile team working on an IoT platform across three time zones. The team uses Kanban with WIP limits, and throughput has been consistent at 12 items per week. Recently, a major enterprise client requested a committed delivery date for a specific feature set, which your sales team communicated would take four weeks. The product owner asks you to guarantee this timeline and wants daily status reports to track progress. Your team has historically avoided commitments because of the variability in item complexity. How should you respond to this request while maintaining agile principles?

Question

Accepted Answer

The correct answer is A. Option A is correct because it uses data-driven forecasting based on actual team performance metrics while maintaining transparency and agile flow principles. Monte Carlo simulation using historical cycle time data can provide probabilistic forecasts (e.g., 85% confidence of completion by week 5) that help stakeholders make informed decisions without forcing artificial commitments that undermine team morale and flow. This approach honors both the business need for predictability and the team's Kanban practice. Regular, transparent updates maintain trust without creating waste through over-reporting. Option C is incorrect because switching methodologies to accommodate one request creates disruption, confusion, and doesn't actually solve the forecasting problem—Scrum sprint commitments are for sprint goals, not long-term feature delivery dates. The problem isn't the framework but the need for probabilistic forecasting. Forcing a framework change treats the symptom rather than using the data already available in the Kanban system.

PMP Practice Question: Process — Agile, Hard

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